Head of Data Quality

At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.

We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

• →Establish Snorkel's quality strategy, standards, and operating model across contributors, datasets, and individual data points.
• →Build the processes, metrics, and governance mechanisms that enable quality to be measured, scaled, and continuously improved.
• →Ensure quality is embedded throughout the DaaS lifecycle and reflected in the commitments we make to customers.
• →Define the standards and operating mechanisms that drive high-quality outcomes across contributors, datasets, and engagements.
• →Partner across Supply, Expert Contributor Experience, Product, and Engineering to operationalize and scale quality throughout the business.
• →Leverage data, automation, and AI-assisted workflows to continuously improve quality, efficiency, and customer outcomes.
• →Establish and scale the Quality function, starting as a hands-on builder and evolving the organization, operating model, and team as the business grows.
• →Serve as a champion for Snorkel's quality approach with customers, prospects, and industry audiences, helping position quality as a key differentiator for the business.

• 8+ years of experience in quality, operations, program management, or a related field, with a track record of building or significantly redesigning quality systems in complex, human-in-the-loop environments.
• Experience defining quality standards, measurement frameworks, and operating processes that drive consistent outcomes at scale.
• Strong analytical and problem-solving skills, including experience using data to measure performance, identify risks, and drive continuous improvement.
• Demonstrated ability to lead through influence and drive cross-functional initiatives across Product, Engineering, Operations, and business teams.
• Excellent communication and stakeholder management skills, with the ability to operate effectively from executive discussions through day-to-day execution.
• Comfortable operating in ambiguity, establishing structure where none exists, and building systems, processes, and teams from the ground up.
• Experience may come from AI data and evaluation organizations, or from other industries that operate complex quality systems at scale, including manufacturing, life sciences, localization, aerospace, or other highly customized production environments.

• Experience building or scaling quality programs for AI data, model evaluation, or other human-in-the-loop AI workflows.
• Familiarity with AI-assisted quality methods, including LLM-as-judge, automated review systems, or other model-assisted approaches.
• Experience operating in environments with evolving requirements, complex task types, or rapidly changing definitions of quality.
• Background in consulting, engineering, operations, or other roles that demonstrate strong first-principles thinking and problem solving.
• Master's degree in a relevant field, or an MBA with an operations or quality focus